如何实现 LLM 和 Chat Model 的流式响应

LangChain为LLMs提供了流式支持。目前，我们支持使用OpenAI，ChatOpenAI和Anthropic实现进行流式传输，在路线图中也计划为其他LLM实现提供流式支持。要使用流式传输，需要实现on_llm_new_token的CallbackHandler 。在这个例子中，我们使用StreamingStdOutCallbackHandler。

from langchain.llms import OpenAI, Anthropic
from langchain.chat_models import ChatOpenAI
from langchain.callbacks.base import CallbackManager
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
from langchain.schema import HumanMessage

llm = OpenAI(streaming=True, callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]), verbose=True, temperature=0)
resp = llm("Write me a song about sparkling water.")

Verse 1
I'm sippin' on sparkling water,
It's so refreshing and light,
It's the perfect way to quench my thirst
On a hot summer night.

Chorus
Sparkling water, sparkling water,
It's the best way to stay hydrated,
It's so crisp and so clean,
It's the perfect way to stay refreshed.

Verse 2
I'm sippin' on sparkling water,
It's so bubbly and bright,
It's the perfect way to cool me down
On a hot summer night.

Chorus
Sparkling water, sparkling water,
It's the best way to stay hydrated,
It's so crisp and so clean,
It's the perfect way to stay refreshed.

Verse 3
I'm sippin' on sparkling water,
It's so light and so clear,
It's the perfect way to keep me cool
On a hot summer night.

Chorus
Sparkling water, sparkling water,
It's the best way to stay hydrated,
It's so crisp and so clean,
It's the perfect way to stay refreshed.

使用 generate 结束的时候，我们仍然可以访问的 LLMResult。但是，对于流式传输，token_usage目前则无法支持。

llm.generate(["Tell me a joke."])

Q: What did the fish say when it hit the wall?
A: Dam!

LLMResult(generations=[[Generation(text='\n\nQ: What did the fish say when it hit the wall?\nA: Dam!', generation_info={'finish_reason': None, 'logprobs': None})]], llm_output={'token_usage': {}, 'model_name': 'text-davinci-003'})

基于 ChatOpenAI 聊天模型的示例:

chat = ChatOpenAI(streaming=True, callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]), verbose=True, temperature=0)
resp = chat([HumanMessage(content="Write me a song about sparkling water.")])

Verse 1:
Bubbles rising to the top
A refreshing drink that never stops
Clear and crisp, it's oh so pure
Sparkling water, I can't ignore

Chorus:
Sparkling water, oh how you shine
A taste so clean, it's simply divine
You quench my thirst, you make me feel alive
Sparkling water, you're my favorite vibe

Verse 2:
No sugar, no calories, just H2O
A drink that's good for me, don't you know
With lemon or lime, you're even better
Sparkling water, you're my forever

Chorus:
Sparkling water, oh how you shine
A taste so clean, it's simply divine
You quench my thirst, you make me feel alive
Sparkling water, you're my favorite vibe

Bridge:
You're my go-to drink, day or night
You make me feel so light
I'll never give you up, you're my true love
Sparkling water, you're sent from above

Chorus:
Sparkling water, oh how you shine
A taste so clean, it's simply divine
You quench my thirst, you make me feel alive
Sparkling water, you're my favorite vibe

Outro:
Sparkling water, you're the one for me
I'll never let you go, can't you see
You're my drink of choice, forevermore
Sparkling water, I adore.

使用 claude模型Anthropic LLM 示例：

llm = Anthropic(streaming=True, callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]), verbose=True, temperature=0)
llm("Write me a song about sparkling water.")

Sparkling water, bubbles so bright,

Fizzing and popping in the light.

No sugar or calories, a healthy delight,

Sparkling water, refreshing and light.

Carbonation that tickles the tongue,

In flavors of lemon and lime unsung.

Sparkling water, a drink quite all right,

Bubbles sparkling in the light.

'\nSparkling water, bubbles so bright,\n\nFizzing and popping in the light.\n\nNo sugar or calories, a healthy delight,\n\nSparkling water, refreshing and light.\n\nCarbonation that tickles the tongue,\n\nIn flavors of lemon and lime unsung.\n\nSparkling water, a drink quite all right,\n\nBubbles sparkling in the light.'